文章基本信息

标题：Solving Lattice Protein Folding Problems by Discrete Particle Swarm Optimization
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作者：Xiao, Jing ; Li, Liangping ; Hu, Xiaomin 等
期刊名称：Journal of Computers
印刷版ISSN：1796-203X
出版年度：2014
卷号：9
期号：8
页码：1904-1913
DOI：10.4304/jcp.9.8.1904-1913
语种：English
出版社：Academy Publisher
摘要：Using computer programs to predict protein structures from a mass of protein sequences is promising for discovering the relationship between the protein construction and their functions. In the area of computational protein structure analysis, the hydrophobic-polar (HP) model is one of the most commonly applied models. The protein folding problem based on HP model has been shown as NP-hard, to handle such an NP-hard problem, this paper proposes a discrete particle swarm optimization algorithm (DPSO_HP) to solve various 2D and 3D HP lattice models-based protein folding problems. The discrete particle swarm optimization method used in DPSO_HP is based on the set concept and the possibility theory from a set-based PSO (S-PSO). A selection strategy incorporating heuristic information and possibilities is adopted in DPSO_HP. A particle’s positions in the algorithm are defined as a set of elements and the velocities of a particle are defined as a set of elements associated with possibilities. The experimental results on a series of 2D and 3D protein sequences show that DPSO_HP is promising and performs better than various competitive state-of-the-art evolutionary algorithms.
关键词：Bioinformatics;Computational intelligence;Discrete particle swarm optimization;Hydrophobic-polar (HP) model;Lattice protein folding